Adaptability of water resources development and utilization to social-economy system in Hunan province, China

The interplay of water resources with social-economy spheres involves a reciprocal feedback mechanism. With the acceleration of the construction process of modernized water networks in Hunan Province, investigating the adaptation status of the "Water-Social-Economy " composite system (WSE) is crucial for promoting sustainability. This study clarifies the connotation of the adaptability of WSE, and the quantitative analyses were conducted through coupling coordinative degree, harmonious development capacity, and the evolution of development lag types among the 14 cities of Hunan Province from 2005 to 2020. The results show that: (1) The development index of the water resources subsystem (WRS) showed a “downward-fluctuation-upward” trend, while the development index of the social-economy subsystem (SES) showed signs of great improvement, the former didn’t catch up with the latter. (2) The coupling coordination degree of WSE developed well, and reached the coordinative development stage by 2020, but the unbalanced spatial pattern between north to south and east to west still exists and is further intensified. (3) The development ability of WSE improved while the harmony ability reduced, and the development rate of WRS and SES hasn’t achieved dynamic synchronization. Finally, the policies and suggestions to improve the adaptability are put forward, which is of instructive significance for the sustainable development of water suitability.

www.nature.com/scientificreports/Hunan Province, an important component of China's water network skeleton, formed a radial river network centered on Dongting Lake (the second largest freshwater lake in China), which is a national strategic reserve base of water resources and flood storage field.However, influenced by various factors such as atmospheric circulation and topography, the spatio-temporal distribution of water resources in Hunan Province is highly uneven.For example, Changsha-Zhuzhou-Xiangtan urban agglomeration gathered over 50% of the province's total GDP, and its water resources utilization ratio has approached the upper limit of 40% with an intensified water resources overload phenomenon.Hengyang-Shaoyang-Loudi drought corridor, an important agricultural production base, the irrigation guarantee rate of which fell below 70%.The existing water infrastructure is relatively weak in ensuring water security, the shrinking of rivers, lakes, and ponds leads to poorer water system connectivity, which makes it more difficult to control ecological pollution and excessive heavy metal, resulting in limited development of the Dongting Lake Economic Belt.On the whole, the construction of inter-basin and inter-region water diversion projects is insufficient, and the interconnected and synchronous-asynchronous cooperated water network pattern has not been formed.According to the "14th Five-Year Water Supply Plan of Hunan Province" and the requirements of modern water network construction, it is necessary to adhere to the comprehensive coordination of water resources and social-economy adaptation relationship, so as to guide the development, utilization, conservation, and management of water resources in Hunan Province in the new era.
Compared with the existing research, this paper focuses on the comprehensiveness of evaluation indexes and the diversity of methods, reflecting the connotation of the appropriateness of water resources and social-economy development as much as possible from multiple perspectives and in-depth in the research, to provide theoretical references and decision-making support for the planning of the coordinated and sustainable development of water resources and social-economy development in Hunan Province of China.
Hunan Province has an average annual precipitation of 1454 mm and a total average water resource of 169.5 billion m 3 .The surface water resources amount to 168.8 billion m 3 , whereas the total available water resources are approximately 83.5 billion m 3 .Due to unstable monsoons and topography, precipitation in Hunan Province exhibits spatial and temporal variations.The rainy season typically lasts only three months throughout the year, accounting for 50 % to 60 % of the annual rainfall.The spatial distribution of annual precipitation shows a general decrease from east to west, with larger amounts in the southern, central, and eastern fringes and smaller amounts in the central-western and northern fringes.With the development of the economy and society, domestic water consumption in Hunan Province has been on a continuous upward trajectory since 1991.Industrial water consumption demonstrates an "inverted U-shaped" phenomenon, characterized by an initial upward trend, reaching a peak, and subsequently declining, in line with the changing trend of the Water Kuznets curve 26 Agricultural water consumption has shown a consistent downward trend since 1991.

Construction of the evaluation framework
The adaptability of water resources and social-economy development refers to the ideal state of coupling coordinated development between water resources utilization and social-economy efficiency under certain periods and scientific & technological conditions, and forms a state of mutual adaptation based on supply-demand balance.There is an interactive and interinhibitive feedback mechanism between the "water-social-economy" composite system (WSE).Water resources support or restrict the development of the social-economy, while the latter would have an important impact on the quantity, quality, and utilization efficiency of the former.The collaborative feedback relationship between the two is shown in Fig. 2.
In this study, a multi-level indicator system is established in a top-down manner, consisting of three levels: the objective, criterion, and indicator levels.This system serves as an evaluation framework for the WSE, composed of two parts: the water resources subsystem (WRS) and the social-economy subsystem (SES).The WRS comprises 3 aspects: (1) Natural occurrence conditions, contains the basic carrying capacity, the impact of climate change, and spatial distribution equilibrium of water resources; (2) Development and utilization degree, mainly measured by the surface and underground water supply capacity and availability; (3) Water consumption, which is reflected in the dependence of domestic, production, and ecology on water resources.The SES comprises 2 aspects: (1) Economic development, mainly linked to GDP and its growth rate, industry output and its proportion, and water use efficiency, etc.; (2) Social structure, generally expressed by population, urbanization, cultivated land service conditions, etc.The specific indicators are presented in Table 1 27,28 .
This study adopts the FAHP-Entropy method-based subjective-objective combination weighting method to determine the weights of the 22 indicators mentioned above.This approach combines subjective attitudes with objectivity to ensure a more rational process for determining the weights of the evaluation system indicators.The specific steps for combining weights using FAHP-Entropy are as follows: 1) The FAHP 29 method is used to weight the indicators.This method utilizes a scale of 0.1 to 0.9 to construct a judgment matrix.Based on the judgment matrix, a fuzzy consistent matrix is further constructed to obtain the subjective weighting vector 2) The entropy 30,31 weighting method is used to weight the indicators.This method calculates the entropy weight of each indicator based on the dispersion of their data using information entropy.The entropy weights are then adjusted based on the contribution of each indicator, resulting in a relatively objective weighting vector 3) The composite weights are calculated 32 .Through computation, the weight of a particular evaluation indicator obtained from the FAHP method is denoted as W 1 , whereas the weight obtained from the entropy weighting method is denoted as W 2 .The composite weight, W z , is then determined by combining these two weights: where α represents the weighting coefficient.Both the FAHP method and entropy weighting method are equally important in determining the composite weight, hence α 1 = α 2 = 0.5.

Improved coupling and coordination evaluation model
To depict the synergistic relationship between water resources and social-economy development, an improved coupling coordination degree (CCD) model 33 is introduced to quantitatively evaluate the coordination and its spatiotemporal variation 34 in the complex water resources system of Hunan Province.The improved CCD model (1) Collaborative evolution and feedback mechanism of the "water-social-economy" composite system.www.nature.com/scientificreports/overcomes the issue of high coupling at low levels by incorporating calculations of the system development index, coupling degree, coordination degree, and coupling coordinative degree.By combining the values of the coupling coordinative degree with the classification criteria of coordination levels, the degree of coupling coordination for each aspect is ultimately determined.First, the development indices for the WRS and SES should be calculated.The development index is a dimensionless value ranging from 0 to 1, designed to reflect the level of system development.The calculation formulas for the two subsystems are as follows: where WR(x) represents the development index of the WRS, while SE y represents the development index of the SES.And x * i , y * i denote the standardized values of the respective evaluation indicators within each subsystem.And ω WR i , ω SE i represent the weights assigned to each evaluation indicator within the two subsystems.And m , n denote the number of evaluation indicators within each subsystem, where, in this case,m = 10 , n = 12.
Based on the calculation of the development indices, the introduced coupling coordination analysis model is used, and different criteria are set to assess the levels of coupling coordination 35 .The coupling and coordination development relationship between the WRS and SES can be classified into different types, as shown in Table 2.
(2) represents the coupling degree, CD coord h represents the coordination degree, and α , β are coefficients that reflect the importance of the subsystems.In this study, we set the coefficient to a certain value to determine its significance, and in this case, α = β = 0.5 .

Harmonious development evaluation model
The harmonious development capacity between the WRS and SES was quantitatively evaluated using the harmonious development evaluation model 36,37 .This model is based on the relationship between the development indices of water resources and social-economy development, and it establishes a rectangular coordinate system in the W-E plane (Fig. 3).The dashed lines y = x 1/3 , y = x , and y = x 3 divide the rectangular region into four equally sized parts from the upper-left corner to the lower-right corner.As indicators of harmonious capacity, the directions indicated by the two red arrows in the figure represent a higher level of harmonious capacity as they approach line y = x .The solid lines y = 1/2 − x 3 , y = 3/4 − x 3 , and y = 1 − x 3 divide the rectangular ( 5)

Improved OECD model
To further illustrate the synergistic relationship between WRS and SES more intuitively, an improved Organization for Economic Co-operation and Development (OECD) model 38 was introduced to assess the development lag types of the WSE system.The OECD model, based on the changes in the system development index, reflects the relationship between the two subsystems, further enhancing the objectivity and accuracy of the driving factors.
where WR represents the rate of change in the development index of the WRS, and SE represents the rate of change in the development index of the SES.
Owing to the sustained high economic growth in Hunan Province from 2005 to 2020, the overall level of economic development has shown a continuous upward trend.Based on the above discussions, this study only considers cases where �SE > 0 .The specific descriptions of the corresponding ε types of development lag are provided in Table 3.
When ε ≥ 1 , it indicates a significant lag in social-economy development compared with the improvement in water resources development, which is called a strong social-economy development lag.When 0.5 < ε < 1 , it indicates that, with economic growth, there is some improvement in water resources, but the former is faster than the latter, resulting in a relatively weak lag in water resources development.When ε < −1 , it indicates a progressive interaction or a strong lag in water resources development within the WSE system.
The technical framework of this study is shown in Fig. 4.

Temporal evolution characteristics of development index
The variation in the development indices for each subsystem of Hunan Province is shown in Criteria for the type of development lag of the WSE system.

Spatial evolution characteristics of development index
According to the spatial evolution of the WRS development level in Hunan Province from 2005 to 2020 (Fig. 6), most areas of Hunan Province exhibited a "fair" or higher level in 2005-2006.From 2007 to 2014, the accelerated industrialization in Hunan Province had a significant adverse impact on the efficient utilization of water resources, resulting in a downgrade of the WRS development level from "fair" to "poor" in most areas of the province.Among them, the minimum precipitation in Hunan Province from 2005 to 2020 occurred in 2011, and during this period, the production methods were relatively extensive.The decrease in precipitation and water pollution issues led to a "poor" water resources development level in all cities of Hunan Province in 2011, representing the lowest level during the period of 2007-2014.
Since 2015, Hunan Province has successively introduced and vigorously implemented a series of water environment restoration policies, including the "Five Major Special Actions for the Comprehensive Treatment of the Dongting Lake Water Environment", the "Three-Year Action Plan for Ecological and Environmental Restoration", and the "Eight-Year Plan for Comprehensive Water Environment Governance".These policies have effectively promoted the overall development of the WRS in the province toward a higher level from 2015 to 2020.In 2018, there was a brief decline in the overall development level in the province, with most cities exhibiting a "poor" level.In 2019, there was some improvement in the southern region of Hunan Province.By 2020, most cities had moved away from the "poor" stage, and it was evident that the WRS development level in the northern part of the province was generally higher than that in the southern part.
From the spatial evolution of the SES development level in Hunan Province from 2005 to 2020 (Fig. 7), Huaihua, Yueyang, and Hengyang cities had SES indices below 0.2 in 2005.The overall development status of the province during this period was its lowest between 2005 and 2020.In the years 2006-2007, Huaihua, Yueyang, and Hengyang cities gradually surpassed the 0.2 threshold in their development indices, indicating a slight improvement in their development status from "poor" to "fairly poor."From 2007 to 2010, most cities remained at a "fairly poor" level for an extended period.During the years 2011-2015, the SES development level in Hunan Province exhibited an uneven and unstable pattern between the north and south regions.In 2014, the overall development level of the province reached "fair", showing a brief improvement.
From 2016 to 2020, due to the accelerated industrial upgrading in Hunan Province, the overall SES development level continued to rise, reaching its highest level within this period in 2020.Apart from cities such as Xiangxi, Changde, Yueyang, and Hengyang, which achieved an "excellent" level in 2020, the remaining areas reached a "good" level.Since the 18th National Congress of the Communist Party of China, under the strong leadership of the Party Central Committee with Comrade Xi Jinping at the core, the entire province has vigorously promoted scientific development, providing strong support for rapid social-economy development.

Temporal evolution characteristics of the coupling coordinative degree
The trend of the coupling coordinative degree (CCD) in the province was influenced by the development index of water resources and could be broadly divided into three stages: 2005-2008, 2009-2016, and 2017-2020.As shown in Fig. 8, the average CCD in most cities and counties during these three stages showed a gradual improvement.
According to Fig. 8, from 2005 to 2013, most cities and counties in Hunan Province were either in a state of coupling imbalance and decline or fluctuating around the threshold of coordination.In 2013, to implement national energy-saving and emission-reduction policies, Hunan Province actively formulated relevant supporting measures, strictly controlled the development and utilization of water resources, phased out low-end production capacity, and vigorously developed water-efficient and high-value-added electronic information industries.During this period, the closure of a large number of high-water-consumption and low-value-added industries led to a significant reduction in water consumption per 10,000 yuan of GDP and water consumption per 10,000 yuan of industrial value added in the province.However, there is still considerable room for further reducing water consumption per 10,000 yuan of GDP and water consumption per 10,000 yuan of industrial value added in industrially weak cities and counties, such as Xiangxi Prefecture, compared with the national average.The In 2018, there was a significant decline in the CCD of most cities, with several even falling below 0.6.However, the CCD of all cities showed a remarkable upward trend in 2019-2020.In 2020, a total of six cities achieved a CCD above 0.8, with Changde City reaching a state of "excellent coordinative coupling".

Spatial evolution characteristics of coupling coordinative degree
According to Fig. 9, the area in the province exhibiting a "barely coupled and declining" level of coordination decreased in 2005-2006.However, during 2005-2009, most cities in Hunan Province still experienced a state of coupling imbalance and decline, indicating an overall lack of optimistic coordination.During 2010-2013, there was some improvement in the CCD in certain areas.However, the overall coordination and development status in the province remained unstable, with many regions oscillating between the states of coupling imbalance and coordinated coupling.
From 2016 to 2019, the overall CCD in the province exhibited a trend of an "initial increase followed by a decline."In 2019, there was a significant difference in the coordinated development between the northern and southern parts of Hunan Province.Most of the northern regions were classified as "barely imbalanced and declining" or "initial and intermediate coupling coordination", while the southern regions were predominantly in the "intermediate coordinated coupling" level.The level of coordinated development in the northern regions was noticeably lower than that in the southern regions.Until 2020, the coordinated development had a leap across the province, with all cities achieving a state of coordinated coupling.
In order to visually illustrate the spatial dispersion of the CCD, this study additionally employed the standard deviation ellipse method 39,40 to analyze the geographical shift 41 in the centroid of the CCD from 2005 to 2020.The results are presented in Fig. 10.The figure reveals that the spatial pattern of the standard deviation ellipse in Hunan Province generally follows a northwest-to-southeast direction.Cities such as Yiyang and Loudi, located within the boundaries of the standard deviation ellipse, are the main areas exhibiting coordinated distribution in Hunan province.In 2020, both the length of the major and minor axes had increased compared with 2005, indicating a slight expansion of the ellipse in both the east-west and north-south directions.Additionally, there was a significant increase in the area of the ellipse in 2020 compared with that in 2005, suggesting a larger relative coverage of the ellipse and an increased disparity in the level of coupling and coordination among different cities within the region. .From 2018 to 2020, the centroid shifted in the direction of "southwest-southeast-northwest," with a noticeable increase in both the magnitude and trend of movement.In general, the centroid of the coordination phenomenon during 2005-2020 deviated to some extent from the geometric center of the province toward the northeast of Hunan Province.This indicates that the northern region of Hunan Province exhibits a higher level of coordination between water resources and economic-social development compared with the southern region.

Analysis of harmonious development capacity and development lag types
Regarding the trend of harmonious development capacity in Hunan Province between 2005 and 2020 (Fig. 11), the position of the harmony degree (H)gradually transitioned from the region bounded by the curves y = x 3 and y = x to the region bounded by the curves y = x 3 and y = x 1/3 , during which it approached the dashed line y = x before gradually diverging, indicating an overall upward trend followed by a decline in harmonious development capacity in Hunan Province from 2005 to 2020.Conversely, the development degree (D) in Hunan Province gradually approached the solid line y = 1 − x 3 , indicating a progressive increase in the harmonious development capacity during this period.
Table 4 presents the calculated results of harmonious development capacity and development lag types for each city in Hunan Province from 2005 to 2020.During 2005-2008, except for Changde and Zhangjiajie cities, which were classified as Type III in terms of developmental lag, the remaining 13 cities in Hunan Province were categorized as Type IV or V.This indicated a significant decline in the development index of WRS in most regions during this stage, reflecting an overall pronounced water resource development lag.
From 2009 to 2016, the development lag types in cities such as Changsha, Zhuzhou, Zhangjiajie, Chenzhou, Yongzhou, and Loudi shifted from water lag to economic lag.Specifically, Changsha City experienced a decrease in HD level, indicating a highly uncoordinated situation between WRS and SES.The HD levels among the other five cities showed an increase, indicating the significant acceleration of WRS development, far outpacing SES development.This suggested a more efficient state of water resource utilization and development to a certain extent.On the other hand, cities such as Xiangtan, Hengyang, Yueyang, and Huaihua transitioned to a relatively weak water lag during this stage, with an overall increasing trend in HD levels.This indicated a certain degree of alleviation of the contradiction between social-economy development and water resource scarcity.However, the economic growth rate outpaced the rate of improvement in water poverty conditions, emphasizing that water resource scarcity remains a significant obstacle that cannot be ignored.
From 2017 to 2020, eight cities including Changsha, Yueyang, Changde, Zhangjiajie, Yiyang, Huaihua, Loudi, and Xiangxi, experienced a WRS development rate that far exceeded the pace of SES, indicating a pronounced economic lag.Furthermore, Chenzhou and Yongzhou cities saw an increase in their economic development rates, which surpassed the concurrent rate of water resource development, indicating a relatively weak water resource development lag.In the situation where the cities of Yueyang, Xiangxi, and Hengyang experienced a lack of synchrony between water resources and the rate of social-economy development, there was a pronounced decrease in HD level, necessitating a particular emphasis on enhanced control.

Discussion
The findings of this paper have some commonalities with previous studies.For example, this paper points out that "the development index of water resources subsystem in Hunan Province shows a decreasing-fluctuatingincreasing trend", which is similar to the conclusion of Yang 42 , who used the TOPSIS model to calculate the development index of water resources.The characteristics of water resources development index of various cities     43 , who used the super-efficient EBM model and GML productivity index as well as dynamic panel quantile regression and other measurement methods.Based on the above comparisons, the conclusions of this paper can be considered to be reliable.Compared with the research of spatio-temporal distribution characteristics of Hunan Province completed by Wang 44 , and evolution of coordinated development of social-economy and water resources utilization of Hunan Province calculated by Yang 45 , the indicators used in this paper are richer, reflecting as much as possible the connotations of the appropriateness of water resources and social-economy development from multiple perspectives.
Based on the results, the following suggestions are made for the adaptability development in Hunan Province.Under the premise of maintaining the implementation of water environment improvement policies in Hunan Province, we should actively guide the transformation of highly polluting factories and encourage tertiary industries with low water consumption, high output value, and more friendly to the environment; and prioritize the development of advanced manufacturing industries with higher value-added products.It is also recommended to promote relevant policies, focusing on breaking down the obstacles of administrative divisions between cities and states, deepening industrial cooperation with neighboring cities, and actively improving the sharing of resources and information across the province.Separate zones for regions with acute conflicts between water supply and demand, and construct cross-basin water transfer projects to relief water shortage, and use high-quality water in the ZiShui River basin to improve water quality.The abundant water resources in western Hunan can be transferred to the economically developed regions like Chang-Zhu-Tan urban agglomeration and the Dongting Lake.The high-quality water resources in the Zishui River basin can be used to relief the water shortages in the Heng-Shao-Lou drought corridor and the Xiangjiang River basin, so as to promote the optimal allocation of water resources and the balanced spatial development of water resources and social-economiy development.For cities with low harmonious development capacity, individual control measures should be carried out to accelerate the structural adjustment, upgrade outdated industries, increase investment in fixed assets, and guide the development of independent innovation.It is necesasary to promote industrial water conservation, and gradually enhance the synchronism and harmonious development capacity between WSR and SES.Furthermore, the spatial distribution of industrial layout and water resources should be coordinated and balanced.

Conclusion
In the study, a comprehensive assessment was conducted from the perspectives of the coordinative relationship, harmonious relationship, and synergistic evolution relationship between water resources utilization and socialeconomy system among 14 administrative regions of Hunan Province from 2005 to 2020.The conclusions are as follows: (1) The WRS development index in various cities of Hunan Province generally exhibited a declining trend, followed by fluctuations before an upward trend, while the SES development index showed a palpable upward trend.(2) From the perspective of the "Water-Social-Economy" system, Hunan Province overall showed a slight upward trend.Presently, all cities have achieved a state of coordinative coupling, indicating a positive direction of development.
(3) The analysis of the evolution of development lag types and harmonious development capacity indicates that the composite "Water-Social-Economy " system in Hunan Province has transitioned from a state of strong water lag in its initial stage, to a state of weak water lag or strong economic lag in the current stage.Simultaneously, the overall harmonious development capacity has shown a trend of an initial increase followed by a decrease.This suggested that the water resources development situation in Hunan Province has improved to some extent.(4) Suggestions for adaptability development were put forward.The transformation and upgrading of industries, construction of water conservancy projects, promotion of water-saving technology could support for the coordinated and sustainable development of "water-social-economy" composite system.
This study can be further deepened as follows: Firstly, the current social-economy and development should be based on the theme of promoting ecological protection and high-quality development.Therefore, the suitability evaluation model should also focus on the competition between water use for living, production, and ecology, so as to avoid crowding out ecological water use in pursuit of development.What's more, the analysis of the spatial suitability of water resources and social-economy was only carried out for the current situation and historical years.Discussion of the WSE development trend after the completion of the water network in the planning year should be included.

Figure 1 .
Figure 1.Overview Map of the Study Area.Graphed by ArcGIS 10.2.Maps of Hunan Province and China were downloaded from Resources and Environment Science and Data Center, Institute of Geographic Sciences and Natural Resources Research, CAS (Open access: https:// www.resdc.cn/).

Fig. 5 .
When calculating the development index, the combined weights of indicators C1-C10 in the WRS were determined as follows: 0.060, 0.076, 0.069, 0.076, 0.079, 0.135, 0.090, 0.092, 0.231, and 0.091.The combined weights of indicators C11-C22 in the SES were determined as follows: 0.065, 0.063, 0.054, 0.100, 0.107, 0.059, 0.064, 0.132, 0.078, 0.143, 0.065, and 0.070.The annual variation trend of the WRS development index in Hunan Province from 2005 to 2020 shows significant fluctuations across different cities over 16 years.The variation trend of the WRS in most areas of the province can be divided into three stages: a noticeable decline from 2005 to 2008, fluctuation within the range of 0.2 to 0.6 from 2009 to 2016, and significant changes occurring from 2017 to 2020.The WRS is primarily influenced by local water resource endowment, the level of development and utilization, water consumption structure, and water-saving policies.The implementation of the "Opinions on Implementing the Strictest Water

ε
> −0.5 III -−1 ≤ ε ≤ −0.5 IV Weaker water resources, development lags behind ε < −1 V Strong water resources, development lags behind Resource Management System" issued by the State Council in 2012 effectively controlled the degree of water resource development and utilization in Hunan Province, resulting in a decline and fluctuation in the WRS development index in most cities.From 2005 to 2020, the annual variation trend of the SES development index in Hunan Province showed an overall significant upward trend in most cities.Since 2005, most areas of the province have experienced a continuous upward trend in the SES development index.After reaching the first peak during the years of 2013-2015, the index continued to rise.Apart from Changsha and Zhangjiajie cities, which reached their highest values in 2019 and 2014, respectively, the other cities in Hunan Province reached their peak values in 2020.In 2020, four cities had SES development indices exceeding 0.8, reaching the "excellent" level.For most cities in Hunan Province, the total GDP has increased by about six times between 2005 and 2020, indicating the robust development of secondary and tertiary industries.This has significantly contributed to the rise in the SES development indices across various cities.

Figure 5 .
Figure 5. Interannual variation trend of the development index in Hunan Province from 2005 to 2020.

Figure 6 .
Figure 6.Spatial distribution of the WRS development level in Hunan Province from 2005 to 2020.Graphed by ArcGIS 10.2 and Adobe Illustrator 2021.

Figure 7 .
Figure 7. Spatial distribution of the SES development level in Hunan Province from 2005 to 2020.Graphed by ArcGIS 10.2 and Adobe Illustrator 2021.

Figure 8 .
Figure 8. Interannual variation trend of the CCD in Hunan Province from 2005 to 2020.

Figure 9 .
Figure 9. Geographical distribution of the CCD in Hunan Province from 2005 to 2020.Graphed by ArcGIS 10.2 and Adobe Illustrator 2021.

Figure 10 .
Figure 10.Interannual variation of the standard deviation ellipse in Hunan Province from 2005 to 2020.Graphed by ArcGIS 10.2, Adobe Illustrator 2021 and Origin 2021.

Figure 11 .
Figure 11.Multi-year changes in the harmonious development capacity in Hunan Province from 2005 to 2020.

Table 1 .
Regional composite system evaluation indices.

Table 2 .
Coupling coordinative degree evaluation level criteria.intofour equally sized parts from the lower-left corner to the upper-right corner.As indicators of development capacity, the directions indicated by the red arrows in the figure show that values closer to 1 represent better development capacity.This model can imply the potential harmony and development trends between the WRS and SES.Based on the connotation of the harmony development model, we calculate the harmony degree H, development degree D, and harmony development degree HD: Figure 3. Schematic diagram of harmonious development model.region

Table 4 .
Harmony development capacity and development lag types in Hunan Province from 2005 to 2020.